Hello, I'm trying to run infercnv for a large integrated dataset with 93+ samples (270,000 cells), however I am running out of memory and the run crashes even by running it in a cluster with parallel computing. I have set the parameters to default based on the available vignettes and video tutorial.
Is there a way to run this code with this much cells faster and use less memory? Will skipping some analyses, such as setting HMM=FALSE, make it run faster?
I can provide my code as well, but was wondering if there is an easy solution to this.
Hello, I'm trying to run infercnv for a large integrated dataset with 93+ samples (270,000 cells), however I am running out of memory and the run crashes even by running it in a cluster with parallel computing. I have set the parameters to default based on the available vignettes and video tutorial.
Is there a way to run this code with this much cells faster and use less memory? Will skipping some analyses, such as setting HMM=FALSE, make it run faster?
I can provide my code as well, but was wondering if there is an easy solution to this.
Best wishes, Constantinos